Research on MDR Concept System Model and Ontology Representation Standardization

doi:10.11885/j.issn.1674-5086.2020.05.22.03

Abstract

Abstract: With the in-depth application of big data and artificial intelligence in various fields, the standardization of knowledge representation has been mentioned as an important agenda. In order to realize the standardization of knowledge representation, this paper introduces the concept of "Three Worlds" model, that is, the real world, the conceptual world and the computer world. According to this model, things in real world can be abstracted concept in concept system model in concept world. Finally, acoording to concrete standards, the concept system model can be tanslated into information model in computer world, so as to realize knowledge representation. In order to standardize the representation of conceptual system model, series standards of ISO/IEC 11179 MDR is studied, the concept system registration meta-model specification is analyzed, and a seven tuple model of MDR concept system is constructed. In addition, the representation method of the relationship between concepts is defined, which lays the foundation for the representation of conceptual system model. In order to transform the concept system model registered in MDR into OWL ontology representation model in the computer world, the rules of mapping MDR concept system to OWL ontology is defined in the paper. Finally, the concept system registration prototype system was designed and developed to verify the feasibility of the MDR concept system and ontology representation. The research results provide a methodology for the standardization of domain knowledge representation.

Key words: knowledge representation, concept system, concept metamodel of MDR, ontology, standardization

CLC Number:

TE341

YUAN Jingshu, LI Hongqi. Research on MDR Concept System Model and Ontology Representation Standardization[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 174-180.

0
/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.11885/j.issn.1674-5086.2020.05.22.03

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y2020/V42/I6/174

References

[1] International Organizati Standardization. Information technology Metadata registries(MDR) Part 1:Framework:ISO/IEC 11179-1-2004[S]. American National Standards Institute, 2004.
[2] International Organizati Standardization. Information technology Metadata registries(MDR) Part 2:Classification:ISO/IEC 11179-2-2005[S]. American National Standards Institute, 2005.
[3] International Organizati Standardization. Information technology Metadata registries(MDR) Part 3:Registry metamodel and basic attributes:ISO/IEC 11179-3-2013[S]. American National Standards Institute, 2013.
[4] International Organizati Standardization. Information technology Metadata registries(MDR) Part 4:Formulation of data definitions:ISO/IEC 11179-4-2004[S]. American National Standards Institute, 2004.
[5] International Organizati Standardization. Information technology Metadata registries(MDR) Part 5:Naming and identification principles, ISO/IEC 11179-5-2005[S]. American National Standards Institute, 2005.
[6] International Organizati Standardization. Information technology-Metadata registries(MDR)-Part 6:Registration, ISO/IEC 11179-6-2005[S]. American National Standards Institute, 2005.
[7] SYLVIE M N N, MATTHIAS L, JÜRGEN S. The ISO/IEC 11179 norm for metadata registries:Does it cover healthcare standards in empirical research?[J]. Journal of Biomedical Informatics, 2013, 46(2):318-327. doi:10.1016/j.jbi.2012.11.008
[8] LEE S, JEONG Dongwon, GIM Jangwon, et al. Canonical sensor ontology builder based on ISO/IEC 11179 for sensor network environments:A standardized approach[J]. International Journal of Distributed Sensor Networks, 2014(5):14. doi:10.1155/2014/790918
[9] 袁满,刘学博,翟红翠. 以概念为中心的自标准数据和标准化数据统一规范化体系模型研究[J]. 情报学报, 2016, 35(3):246-253. doi:10.3772/j.issn.1000-0135.2016.003.003 YUAN Man, LIU Xuebo, ZHAI Hongcui. Research on concept-centered unified standardization system model of self-standard data and standardized data[J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(3):246-253. doi:10.3772/j.issn.1000-0135.2016.003.003
[10] 中国电子技术标准化研究院全国信息技术标准化技术委员会大数据标准工作组. 大数据标准化白皮书[EB/OL].[2018-03-01]. http://www.cesi.ac.cn/images/editor/20180124/20180124135528742.pdf. BIG Data Standard Work Group of National Information Technology Standardization Technology Committee of China Institute of Electronic Technology Standardization. Big data standardization white paper[EB/OL].[2018-03-01]. http://www.cesi.ac.cn/images/editor/2018-0124/20180124135528742.pdf.
[11] 中国电子技术标准化研究院. 知识图谱标准化白皮书[EB/OL].[2019-09-11]. http://www.cesi.cn/images/editor/20190911/20190911094806634.pdf. China Institute of Electronic Technology Standardization. White paper on standardization of knowledge graph[EB/OL].[2019-09-11]. http://www.cesi.cn/images/editor/20190911/20190911094806634.pdf.
[12] 中国电子技术标准化研究院. 人工智能标准化白皮书[EB/OL].[2018-04-04]. http://www.cesi.cn/images/editor/20180402/20180402120211919.pdf. China Institute of Electronic Technology Standardization. White paper on standardization of artificial intelligence[EB/OL].[2018-04-04]. http://www.cesi.cn/images/editor/20180402/20180402120211919.pdf.
[13] 袁满,王梅. 石油数据组织与分析[M]. 青岛:中国石油大学出版社, 2016. YUAN Man, WANG Mei. Petroleum data organization and analysis[M]. Qingdao:China University of Petroleum Press, 2016.
[14] 王珊,萨师煊. 数据库系统概论[M]. 北京:高等教育出报社, 2010. WANG Shan, SA Shixuan. An introduction to database system[M]. Beijing:Higher Education Press, 2010.
[15] 中国标准研究中心. 术语工作:GB/T 15237.1-2000[S]. 北京:中国标准出版社, 2000. China Standards Research Center. Terminology work:GB/T 15237.12000[S]. Beijing:China Standards Publishing House, 2000.
[16] 冯志伟. 术语学中的概念系统与知识本体[J]. 术语标准化与信息技术, 2006(1):9-15. doi:10.3969/j.issn.1007-2489.2006.01.003 FENG Zhiwei. Conception system and ontology in terminology[J]. Terminology Standardization and Information Technology, 2006(1):9-15. doi:10.3969/j.issn.1007-2489.2006.01.003
[17] International Standard. Terminology work-Vocabulary-Part 1:Theory and application:ISO 1087-1[S]. 1st ed. 2010.
[18] THOMAS R G. A translation approach to portable ontology knowledge specification[J]. Knowledge Acquistion, 1993, 5(2):199-220. doi:10.1006/knac.1993.1008
[19] STUDER R, BENJAMINS V R, FENSEL D. Knowledge engineering:Principles and methods[J]. Data & Knowledge Engineering, 1998, 25(1-2):161-197.10.1016/S0169-023X(97)00056-6
[20] 余凡. 领域本体构建方法及实证研究[M]. 武汉:武汉大学出版社, 2015. YU Fan. Domain ontology construction method and empirical research[M]. Wuhan:Wuhan University Press, 2015.
[21] NATALYA F. A gruide to creating your first ontology[EB/OL].[2016-01-20]. http://www.Protégé.Stanford.edu/publications/ontology_development/ontology-101.pdf.
[22] MAEDCHE A, STAAB S. Ontology learning for the semantic web[J]. IEEE Intelligent Systems, 2002, 16(2):72-79. doi:10.1109/5254.920602
[23] 胡兆芹. 本体与知识组织[M]. 北京:中国文史出版社, 2014. HU Zhaoqin. Ontology and knowledge organization[M]. Beijing:Chinese Literature and History Publishing House, 2014.